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Flow Control

Flow Control. receiver: explicitly informs sender of (dynamically changing) amount of free buffer space RcvWindow field in TCP segment sender: keeps the amount of transmitted, unACKed data less than most recently received RcvWindow. flow control. TCP Flow Control. sender won’t overrun

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Flow Control

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  1. Flow Control

  2. receiver: explicitly informs sender of (dynamically changing) amount of free buffer space RcvWindow field in TCP segment sender: keeps the amount of transmitted, unACKed data less than most recently received RcvWindow flow control TCP Flow Control sender won’t overrun receiver’s buffers by transmitting too much, too fast RcvBuffer= size or TCP Receive Buffer RcvWindow = amount of spare room in Buffer receiver buffering

  3. TCP Flow Control: How it Works spare room in buffer = RcvWindow source port # dest port # sequence number acknowledgement number head len not used rcvr window size U A P R S F checksum ptr urgent data Options (variable length) application data (variable length) 3

  4. TCP: setting timeouts

  5. Q: how to set TCP timeout value? longer than RTT note: RTT will vary too short: premature timeout unnecessary retransmissions too long: slow reaction to segment loss Q: how to estimate RTT? SampleRTT: measured time from segment transmission until ACK receipt ignore retransmissions, cumulatively ACKed segments SampleRTT will vary, want estimated RTT “smoother” use several recent measurements, not just current SampleRTT TCP Round Trip Time and Timeout

  6. High-level Idea Set timeout = average + safe margin

  7. Estimating Round Trip Time • SampleRTT: measured time from segment transmission until ACK receipt • SampleRTT will vary, want a “smoother” estimated RTT use several recent measurements, not just current SampleRTT EstimatedRTT = (1- )*EstimatedRTT + *SampleRTT • Exponential weighted moving average • influence of past sample decreases exponentially fast • typical value:  = 0.125

  8. Setting Timeout Problem: using the average of SampleRTT will generate many timeouts due to network variations Solution: EstimtedRTT plus “safety margin” large variation in EstimatedRTT -> larger safety margin freq. RTT DevRTT = (1-)*DevRTT + *|SampleRTT-EstimatedRTT| (typically,  = 0.25) Then set timeout interval: TimeoutInterval = EstimatedRTT + 4*DevRTT

  9. An Example TCP Session

  10. Setting the timeout EstimtedRTT plus “safety margin” large variation in EstimatedRTT -> larger safety margin TCP Round Trip Time and Timeout EstimatedRTT = (1-x)*EstimatedRTT + x*SampleRTT • Exponential weighted moving average • influence of given sample decreases exponentially fast • typical value of x: 0.1 Timeout = EstimatedRTT + 4*Deviation Deviation = (1-x)*Deviation + x*|SampleRTT-EstimatedRTT|

  11. Fast retransmit

  12. Fast Retransmit Timeout period often relatively long: long delay before resending lost packet Detect lost segments via duplicate ACKs sender often sends many segments back-to-back if segment is lost, there will likely be many duplicate ACKs If sender receives 3 ACKs for the same data, it supposes that segment after ACKed data was lost: resend segment before timer expires 12

  13. 4 4 4 Triple Duplicate Ack Packets 1 7 2 3 4 5 6 Acknowledgements (waiting seq#) 2 3 4 13

  14. Fast Retransmit: event: ACK received, with ACK field value of y if (y > SendBase) { … SendBase = y if (there are currently not-yet-acknowledged segments) start timer … } else { increment count of dup ACKs received for y if (count of dup ACKs received for y = 3) { resend segment with sequence number y … a duplicate ACK for already ACKed segment fast retransmit 14

  15. Congestion Control

  16. Congestion: informally: “too many sources sending too much data too fast for network to handle” manifestations: lost packets (buffer overflow at routers) long delays (queuing in router buffers) a highly important problem! Principles of Congestion Control

  17. two senders, two receivers one router, infinite buffers no retransmission Causes/costs of congestion: scenario 1

  18. Throughput increases with load Maximum total load C (Each session C/2) Large delays when congested The load is stochastic Causes/costs of congestion: scenario 1

  19. one router, finite buffers sender retransmission of lost packet Causes/costs of congestion: scenario 2

  20. always: (goodput) Like to maximize goodput! “perfect” retransmission: retransmit only when loss: Actual retransmission of delayed (not lost) packet makes larger (than perfect case) for same l l l > = l l l in in in out out out Causes/costs of congestion: scenario 2

  21. Causes/costs of congestion: scenario 2 out out out ’in ’in “costs” of congestion: • more work (retrans) for given “goodput” • unneeded retransmissions: link carries (and delivers) multiple copies of pkt

  22. four senders multihop paths timeout/retransmit l l in in Causes/costs of congestion: scenario 3 Q:what happens as and increase ?

  23. Causes/costs of congestion: scenario 3 Another “cost” of congestion: • when packet dropped, any “upstream” transmission capacity used for that packet was wasted!

  24. End-end congestion control: no explicit feedback from network congestion inferred from end-system observed loss, delay approach taken by TCP Network-assisted congestion control: routers provide feedback to end systems single bit indicating congestion (SNA, DECbit, TCP/IP ECN, ATM) explicit rate sender should send at Approaches towards congestion control Two broad approaches towards congestion control:

  25. Goals of congestion control • Throughput: • Maximize goodput • the total number of bits end-end • Fairness: • Give different sessions “equal” share. • Max-min fairness • Maximize the minimum rate session. • Single link: • Capacity R • sessions m • Each sessions: R/m

  26. Max-min fairness • Model: Graph G(V,e) and sessions s1 … sm • For each session sia rate riis selected. • The rates are a Max-Min fair allocation: • The allocation is maximal • No ri can be simply increased • Increasing allocation rirequires reducing • Some session j • rj ≤ ri • Maximize minimum rate session.

  27. Max-min fairness: Algorithm • Model: Graph G(V,e) and sessions s1 … sm • Algorithmic view: • For each link compute its fair share f(e). • Capacity / # session • select minimal fair share link. • Each session passing on it, allocate f(e). • Subtract the capacities and delete sessions • continue recessively. • Fluid view.

  28. Max-min fairness • Example • Throughput versus fairness.

  29. ABR: available bit rate: “elastic service” if sender’s path “underloaded”: sender can use available bandwidth if sender’s path congested: sender lowers rate a minimum guaranteed rate Aim: coordinate increase/decrease rate avoid loss! Case study: ATM ABR congestion control

  30. RM (resource management) cells: sent by sender, in between data cells one out of every 32 cells. RM cells returned to sender by receiver Each router modifies the RM cell Info in RM cell set by switches “network-assisted” 2 bit info. NI bit: no increase in rate (mild congestion) CI bit: congestion indication (lower rate) Case study: ATM ABR congestion control

  31. two-byte ER (explicit rate) field in RM cell congested switch may lower ER value in cell sender’ send rate thus minimum supportable rate on path EFCI bit in data cells: set to 1 in congested switch if data cell preceding RM cell has EFCI set, sender sets CI bit in returned RM cell Case study: ATM ABR congestion control

  32. How does the router selects its action: selects a rate Set congestion bits Vendor dependent functionality Advantages: fast response accurate response Disadvantages: network level design Increase router tasks (load). Interoperability issues. Case study: ATM ABR congestion control

  33. End to end control

  34. End to end feedback • Abstraction: • Alarm flag. • observable at the end stations

  35. Simple Abstraction

  36. Simple Abstraction

  37. Simple feedback model • Every RTT receive feedback • High Congestion Decrease rate • Low congestion Increase rate • Variable rate controls the sending rate.

  38. Multiplicative Update • Congestion: • Rate = Rate/2 • No Congestion: • Rate= Rate *2 • Performance • Fast response • Un-fair: Ratios unchanged

  39. Additive Update • Congestion: • Rate = Rate -1 • No Congestion: • Rate= Rate +1 • Performance • Slow response • Fairness: • Divides spare BW equally • Difference remains unchanged

  40. overflow AIMD Scheme • Additive Increase • Fairness: ratios improves • Multiplicative Decrease • Fairness: ratio unchanged • Fast response • Performance: • Congestion - Fast response • Fairness

  41. AIMD: Two users, One link Fairness Rate of User 2 BW limit Rate of User 1

  42. TCP Congestion Control • Closed-loop, end-to-end, window-based congestion control • Designed by Van Jacobson in late 1980s, based on the AIMD alg. of Dah-Ming Chu and Raj Jain • Works well so far: the bandwidth of the Internet has increased by more than 200,000 times • Many versions • TCP/Tahoe: this is a less optimized version • TCP/Reno: many OSs today implement Reno type congestion control • TCP/Vegas: not currently used For more details: see TCP/IP illustrated; or readhttp://lxr.linux.no/source/net/ipv4/tcp_input.c for linux implementation 42

  43. TCP/Reno Congestion Detection • Detect congestion in two cases and react differently: • 3 dup ACKs • timeout event Philosophy: • 3 dup ACKs indicates network capable of delivering some segments • timeout is “more alarming”

  44. Basic Structure • Two “phases” • slow-start: MI • congestion avoidance: AIMD • Important variables: • cwnd: congestion window size • ssthresh: threshold between the slow-start phase and the congestion avoidance phase

  45. Visualization of the Two Phases

  46. Slow Start: MI • What is the goal? • getting to equilibrium gradually but quickly • Implements the MI algorithm • doublecwnd every RTT until network congested get a rough estimate of the optimal of cwnd

  47. segment 1 cwnd = 1 ACK for segment 1 segment 2 segment 3 ACK for segments 2 + 3 segment 4 segment 5 segment 6 segment 7 Slow-start Initially: cwnd = 1; ssthresh = infinite (e.g., 64K); For each newly ACKed segment: if (cwnd < ssthresh) /* slow start*/ cwnd = cwnd + 1; cwnd = 2 cwnd = 4 cwnd = 6 cwnd = 8

  48. Startup Behavior with Slow-start See [Jac89]

  49. TCP/Reno Congestion Avoidance Maintains equilibrium and reacts around equilibrium Implements the AIMD algorithm increases window by 1 per round-trip time (how?) cuts window size to half when detecting congestion by 3DUP to 1 if timeout if already timeout, doubles timeout 49

  50. TCP/Reno Congestion Avoidance Initially: cwnd = 1; ssthresh = infinite (e.g., 64K); For each newly ACKed segment: if (cwnd < ssthresh) /* slow start*/ cwnd = cwnd + 1; else /* congestion avoidance; cwnd increases (approx.) by 1 per RTT */ cwnd += 1/cwnd; Triple-duplicate ACKs: /* multiplicative decrease */ cwnd = ssthresh = cwnd/2; Timeout: ssthresh = cwnd/2; cwnd = 1; (if already timed out, double timeout value; this is called exponential backoff) 50

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